Drug prescription and administration processes strongly impact on the occurrence of risks in medical settings for they can be sources of adverse drug events (ADEs). A properly engineered use of information and communication technologies has proven to be a promising approach to reduce these risks. In this study, we propose PHARMA, a web information system which supports healthcare staff in the secure cooperative execution of drug prescription, transcription and registration tasks. PHARMA allows the easy sharing and management of documents containing drug-related information (i.e., drug prescriptions, medical reports, screening), which is often inconsistent and scattered across different information systems and heterogeneous organization domains (e.g., departments, other hospital facilities). PHARMA enables users to access such information in a consistent and secure way, through the adoption of REST and web-oriented design paradigms and protocols. We describe the implementation of the PHARMA prototype, and we discuss the results of the usability evaluation that we carried out with the staff of a hospital in Florence, Italy.

The rational use and management of energy is a key objective for the evolution towards the smart grid. In particular in the private home domain the adoption of wide-scale energy consumption monitoring techniques can help end users in optimizing energy consumption behaviors. While most existing approaches for load disaggregation and classification requires high-frequency monitoring data, in this paper we propose an approach for detecting and identifying the appliances in use by analysing low-frequency monitoring data gathered by meters (i.e. smart plugs) distributed in the home. Our approach implements a supervised classification algorithm with artificial neural networks and has been tested with a dataset of power traces collected in real-world home settings.

The technological advances in hardware and software communication technologies are speeding up the path towards the actualization of the Internet of Things. Nonetheless, novel requirements are emerging for the effective and efficient usage of the huge amount of available sensor information and functional capabilities. Several approaches have been proposed for leveraging the Web to this purpose (i.e. Web of Things). In this work, we propose an information-centric approach to enable a Web of Sensors. We combine the principles of Linked Data and Representational State Transfer (REST) architectural style to represent sensors as graphs of URI-addressable information nodes, which can be easily combined and reused for developing novel applications and creating software-based sensors (Virtual Sensors). Our approach relies on the adoption of a web-oriented middleware and information model, called InterDataNet.

Continuous care models for chronic diseases pose several technology-oriented challenges for home-based care, where assistance services rely on a close collaboration among different stakeholders, such as health operators, patient relatives, and social community members. This paper describes an ontology-based context model and a related context management system providing a configurable and extensible service-oriented framework to ease the development of applications for monitoring and handling patient chronic conditions. The system has been developed in a prototypal version, and integrated with a service platform for supporting operators of home-based care networks in cooperating and sharing patient-related information and coordinating mutual interventions for handling critical and alarm situations. Finally, we discuss experimentation results and possible further research directions.

Care models for chronic condition treatment place point-of-care in the community and at patient's home and imply an organized care system ("continuous care network"). The contribution of this work consists in the proposal of a service framework to support information acquisition, integration and sharing in continuous care networks. The framework is based on a service-oriented message-oriented middleware ("SAI middleware") easing the development of context-aware and information integration applications. We describe an ongoing case study aiming at demonstrating the use of the service framework in a reference application scenario for patient conditions monitoring, alarm detection and policy-based handling.

Several mobile guides exist providing tourists with location-based content delivery. This paper presents a novel mobile application, named InfoTour, aiming at enriching touristspsila experiences by supporting social interactions among tourists and by enabling seamless interaction with third-party service and data providers. The proposed system is based on service oriented architecture principles, and we describe here the main issues related to the system prototype design and development.

In this work we propose a procedure for the estimation of the spatial distribution of the rainfall rate in the observation time T over an area covered by a meteorological radar and a raingauge network. T can be the whole duration of a rainfall phenomenon or a part of it. The procedure is applied to a data set composed by PPI scans of absolute reflectivity gathered by a weather radar and by point rainfall measurement as provided by a raingauge network over the area monitored by the radar. The procedure was applied and tested on a experimental dataset related to a one-day precipitation phenomenon observed in Tuscany (Italy) on 29 October 1999, along the Arno river basin. The performance of the proposed procedure has been evaluated assuming a subset of the raingauge network as "true" rainfall rate reference

We propose the utilization of a satellite system, composed by a couple of LEO (low Earth orbit) satellites operating in the 18-22 GHz range (close to the 22.235 GHz absorption line of water vapor), to estimate the total content of water vapor (IWV, integrated water vapor) along the propagation path between the two satellites (one of them carrying a transmitter, the other a receiver). In particular, we show that IWV can be estimated starting from measurements of received spectral power.

The authors describe a differential method for estimating mean concentrations of atmospheric molecular components along a quasivertical rectilinear Earth-air path utilizing a transmitter-receiver pair operating at infrared. The choice of a differential method is due to the need to limit calibration problems without utilizing more complex and costly systems such as DIAL, whose capabilities are definitely oversized for this kind of measurement. For this objective, a preliminary selection of the optimal wavenumbers for each molecular species of interest is needed. This is the main issue discussed in this paper, after which the analysis focuses on the effects of the uncertainties on atmospheric parameters that need to be estimated to provide the final mean-concentration estimates. The feasibility study is carried out on carbon monoxide, considered as test species of interest in the reported simulations of atmospheric propagation, based on standard atmospheric models. Technological requirements are finally discussed.

The authors address the problem of estimating vertical profiles of atmospheric water vapor by means of attenuation measurements simultaneously made at different frequencies along a vertical satellite-ground link. The operating frequencies selected are those around the spectral absorption lines of water vapor at 22.235 GHz. A simulation is presented of multifrequency attenuation measurements, based on an atmospheric propagation model and on radiosonde data providing true profiles of temperature, pressure, and water vapor. The results indicate that such multifrequency measurements are correlated to variations of the vertical profiles of water vapor. It is therefore expected that vertical detail of such profiles depends on number and position of the frequencies utilized.

In this paper, we analyze the feasibility and performance of a particular tomographic system for atmospheric pollution monitoring over limited areas (e.g., urban areas). Such a system exploits attenuation-based infrared measurements of the average concentration of the fundamental molecular species of pollutants along rectilinear paths. First, the paper demonstrates the feasibility of an apparatus based on semiconductor infrared laser diode transmitters and passive retroreflectors, capable of measuring the average concentration of pollutants along rectilinear paths with 2-km maximum length, by exploiting their infrared absorption properties. For each gaseous species of interest, the optimal wavelength is then singled out, with the purpose of applying the derivative method for measuring the corresponding average atmospheric concentration. The optimal wavelengths are determined based on both absorption data of atmospheric components and plausible ranges of variation of their concentration. Finally, we present simulations carried out to evaluate the reconstruction of spatial-concentration fields of several air pollutants obtained through a tomographic-inversion algorithm exploiting simultaneous attenuation measurements made along different infrared links. Two different network topologies for such measurements are considered.

The authors analyze the feasibility and performance of a particular tomographic system for atmospheric pollution monitoring over limited areas (e.g. urban areas). Such a system exploits attenuation-based infrared measurements of the average concentration of the fundamental molecular species of pollutants along rectilinear paths. First, the paper demonstrates the feasibility of an apparatus based on semiconductor infrared laser diode transmitters and passive retroreflectors, capable of measuring the average concentration of pollutants along rectilinear paths with 2 km maximum length, by exploiting their infrared absorption properties. For each gaseous species of interest, the optimal wavelength is then singled out, with the purpose of applying the derivative method for measuring the corresponding average atmospheric concentration. The optimal wavelengths are determined based on both absorption data of atmospheric components and plausible ranges of variation of their concentration. Finally, the authors present simulations carried out to evaluate the reconstruction of spatial concentration fields of several air pollutants, obtained through a tomographic inversion algorithm exploiting simultaneous attenuation measurements made along different infrared links. Two different network topologies for such measurements are considered.

The microwave tomographic inversion technique (MTIT) proposed in 1991 for reconstruction of rainfall fields at ground through microwave attenuation measurements is reconsidered. A new algorithm for data inversion is presented [referred to as stochastic reconstruction technique (SRT)] that generally performs better than the one originally adopted [referred to as arithmetic reconstruction technique (ART)]. Improvement is achieved in spatial definition and general reliability of rainfall field reconstruction. The new model adopted to represent the reconstructed rainfall fields leads to a completely different strategy for the inversion problem, and this strategy is based on a global optimization stochastic technique (GOST). Results obtained through the SRT-MTIT are presented in the paper and compared to those obtained by employing the ART-MTIT. It also is shown that, based on the SRT-MTIT approach, fast and reliable time tracking of rainfall events is made possible by exploiting previous reconstructions and by the improved long-term physical consistency of the model adopted for rainfall field decomposition.

Polarization, together with the amplitude, time, frequency, phase, and bearing descriptors of radar signals, completes the information which can be obtained on target returns in monostatic radars. The exploitation of information on the echo polarization state through polarimetric radars is currently a subject of interest, due to theoretical and technological advances, as well as to the development of new radar applications. Many polarization techniques, which have been proposed and analyzed to enhance radar performance, are reviewed in this paper in order to assess the possible improvement they can provide in the signal-to-disturbance ratio, target detectability, target discrimination and resolution, and target classification and identification. Some recent experimentally based results relating to these applications are also presented. Those techniques are emphasized for which polarization-based capabilities appear sufficiently assessed, such as adaptive polarization cancellation of clutter, chaff, and jamming. Polarization Doppler processing of dual-polarization radar signals, meteorologic applications, and polarization adaptation for target detection in the clear (in free space) are also examined.